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split torch.testing._internal.* and add type checking for torch.testing._internal.common_cuda (#44575)
Summary: First step to fix https://github.com/pytorch/pytorch/issues/42969. Pull Request resolved: https://github.com/pytorch/pytorch/pull/44575 Reviewed By: malfet Differential Revision: D23668740 Pulled By: walterddr fbshipit-source-id: eeb3650b1780aaa5727b525b4e6182e1bc47a83f
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mypy.ini
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mypy.ini
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@ -53,7 +53,55 @@ ignore_errors = True
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[mypy-torch.distributed.*]
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[mypy-torch.distributed.*]
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ignore_errors = True
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ignore_errors = True
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[mypy-torch.testing._internal.*]
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[mypy-torch.testing._internal.te_utils.*]
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ignore_errors = True
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[mypy-torch.testing._internal.dist_utils.*]
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ignore_errors = True
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[mypy-torch.testing._internal.codegen.*]
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ignore_errors = True
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# [mypy-torch.testing._internal.common_cuda.*]
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# ignore_errors = True
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[mypy-torch.testing._internal.common_quantized.*]
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ignore_errors = True
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[mypy-torch.testing._internal.common_distributed.*]
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ignore_errors = True
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[mypy-torch.testing._internal.jit_utils.*]
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ignore_errors = True
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[mypy-torch.testing._internal.common_device_type.*]
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ignore_errors = True
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[mypy-torch.testing._internal.autocast_test_lists.*]
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ignore_errors = True
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[mypy-torch.testing._internal.hypothesis_utils.*]
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ignore_errors = True
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[mypy-torch.testing._internal.common_methods_invocations.*]
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ignore_errors = True
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[mypy-torch.testing._internal.jit_metaprogramming_utils.*]
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ignore_errors = True
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[mypy-torch.testing._internal.common_nn.*]
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ignore_errors = True
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[mypy-torch.testing._internal.common_quantization.*]
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ignore_errors = True
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[mypy-torch.testing._internal.common_utils.*]
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ignore_errors = True
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[mypy-torch.testing._internal.generated.*]
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ignore_errors = True
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[mypy-torch.testing._internal.distributed.*]
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ignore_errors = True
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ignore_errors = True
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[mypy-torch.quantization.observer]
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[mypy-torch.quantization.observer]
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@ -10,7 +10,7 @@ import contextlib
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TEST_CUDA = torch.cuda.is_available()
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TEST_CUDA = torch.cuda.is_available()
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TEST_MULTIGPU = TEST_CUDA and torch.cuda.device_count() >= 2
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TEST_MULTIGPU = TEST_CUDA and torch.cuda.device_count() >= 2
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CUDA_DEVICE = TEST_CUDA and torch.device("cuda:0")
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CUDA_DEVICE = torch.device("cuda:0") if TEST_CUDA else None
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# note: if ROCm is targeted, TEST_CUDNN is code for TEST_MIOPEN
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# note: if ROCm is targeted, TEST_CUDNN is code for TEST_MIOPEN
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TEST_CUDNN = TEST_CUDA and torch.backends.cudnn.is_acceptable(torch.tensor(1., device=CUDA_DEVICE))
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TEST_CUDNN = TEST_CUDA and torch.backends.cudnn.is_acceptable(torch.tensor(1., device=CUDA_DEVICE))
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TEST_CUDNN_VERSION = torch.backends.cudnn.version() if TEST_CUDNN else 0
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TEST_CUDNN_VERSION = torch.backends.cudnn.version() if TEST_CUDNN else 0
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